# Research Engineer at Metis, Inc

> United States · Unspecified · ML / AI · open. Source: https://alderhq.app/jobs/greenhouse%3Ametisinc%3A4034476009 (read 2026-11-14).

## Facts (observed)

- Company: [Metis, Inc](https://alderhq.app/companies/metis-inc)
- Location text: San Francisco, California; SF
- Where it can be done from (inferred): United States (evidence: "Location: San Francisco, California; SF")
- Posted: 2025-10-06 (403 days ago)
- First seen by alder: 2026-11-07 · last verified: 2026-11-07
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://job-boards.greenhouse.io/metisinc/jobs/4034476009
- Skills listed (inferred): Python, PyTorch, TensorFlow

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (SF Bay Area, n 560): p25 $200k, median $245k, p75 $300k

## Description (the employer's text)

### About the Role

As a Research Engineer at Metis, you’ll work on building the next generation of autonomous post-training systems that leverage our Mantis platform. You’ll operate at the intersection of cutting-edge ML research and scalable engineering, designing, implementing, and deploying algorithms that improve how AI agents learn from feedback, synthetic data, and real-world interactions.

You’ll move seamlessly between papers and production, leading large-scale experiments, creating optimized training pipelines, and helping shape the future of post-training autonomy. You’ll have significant ownership, high compute budgets, and the mandate to push the state of the art in applied reinforcement and preference optimization.

### What You'll Do

- Research and help build an autonomous post-training agent leveraging the Mantis platform
- Design and execute large-scale experiments on synthetic data generation and algorithmic architecture
- Develop and refine methods for reinforcement learning, reward modeling, and human feedback integration
- Collaborate cross-functionally with Core and Platform Engineering to deploy and evaluate models in production settings
- Publish or contribute to leading-edge research in the post-training domain
- Use tooling and compute efficiently to iterate on experimental pipelines and accelerate research velocity
### Requirements

- Deep experience in machine learning, preferably reinforcement learning, post-training, or alignment research
- Demonstrated research contributions; ideally published papers (ICML, NeurIPS) or public implementations
- Strong proficiency in Python and ML frameworks (PyTorch, JAX, or TensorFlow)
- Comfort with distributed training, high-throughput data pipelines, and large-scale experiment management
- Ability to reason independently, formulate hypotheses, and run experiments from idea → insight → product impact
### Compensation & Benefits

- Base: $200,000–$1,000,000
- Significant Equity
- Full medical, dental, and vision
- Wellness & L&D stipend
- Equinox membership
- Breakfast, lunch, and dinner provided (Unlimited Doordash)
- $25,000 housing stipend
### About Metis

Metis helps enterprises and labs build the most reliable AI agents by leveraging post-training. Our platform enables the creation, improvement, and deployment of the most capable frontier agents designed for rigorous, real-world workflows.

Momentum

- 0 → six-figure monthly revenue in the last six weeks
- Working with several Fortune 500 enterprises & frontier AI labs
- Growing 150%+ MoM
Backed by

Y Combinator, CRV, and executives from OpenAI, Google, Mercor, NVIDIA, and others.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Ametisinc%3A4034476009 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.